Nowadays, the functions of smart phones are more diversified. For example, the smart phones with a voice wakeup function are favored by most consumers. For example, when the smart phone in a sleep state receives a voice of a keyword from the user, the smart phone starts to recognize the keyword. If the keyword is authenticated, the smart phone is switched from the sleep state to a normal working state. In other words, the user can wake up the smart phone or other electronic products without the need of pressing any function key of the smart phone.
FIG. 1 is a block diagram illustrating a voice wakeup detecting device 100 of an electronic product according to the prior art. The voice wakeup detecting device 100 comprises a front end detecting circuit 110, a speech recognition processor 120 and a main processor 130. The front end detecting circuit 110 comprises a microphone 102 and an event detector 104. In a sleep state, the front end detecting circuit 110 is still powered, and the microphone 102 and the event detector 104 are continuously operated. Generally, the process of waking up the electronic product comprises the following three detection phases.
The event detector 104 performs acoustic event detection. The microphone 102 is an analog microphone for generating a voice signal Sa to the event detector 104. The event detector 104 detects the amplitude, the signal-to-noise ratio (SNR) or the sub-band SNR of the voice signal Sa.
When the electronic product is in the sleep state and the voice wakeup detecting device 100 is in a first detection phase, the microphone 102 continuously receives the ambient voice and converts the ambient voice into the voice signal Sa. The voice signal Sa is transmitted to the event detector 104. If the amplitude of the voice signal Sa is higher than a threshold value, the event detector 104 generates a first interrupt signal INT1 to the speech recognition processor 120.
Alternatively, the event detector 104 may detect the signal-to-noise ratio (SNR) or the sub-band SNR of the voice signal Sa. For example, if the SNR or the sub-band SNR of the voice signal Sa is higher than a threshold value, the event detector 104 generates the first interrupt signal INT1 to the speech recognition processor 120.
An example of the speech recognition processor 120 is a digital signal processor (DSP), which is also referred to a tiny processor. The speech recognition processor 120 performs a speech recognition on the voice signal Sa. If the first interrupt signal INT1 is not asserted, the speech recognition processor 120 is not powered and thus disabled. Meanwhile, the voice wakeup detecting device 100 is in the first detection phase. Whereas, if the first interrupt signal INT1 is asserted, the speech recognition processor 120 is enabled. Consequently, the detection phase of the voice wakeup detecting device 100 is changed from the first detection phase to a second detection phase so as to perform the speech recognition of recognizing the keyword of the voice signal Sa.
In the second detection phase, the speech recognition processor 120 judges whether the voice signal Sa is the voice of the keyword. After the speech recognition processor 120 receives the voice signal Sa and performs an analog-to-digital conversion on the voice signal Sa, the speech recognition processor 120 starts to recognize the keyword. If the speech recognition processor 120 confirms that the voice signal Sa is the voice of the keyword, the speech recognition processor 120 generates a second interrupt signal INT2 to the main processor 130. After the main processor 130 receives the second interrupt signal INT2, the detection phase of the voice wakeup detecting device 100 is changed from the second detection phase to a third detection phase.
Whereas, if the speech recognition processor 120 judges that the voice signal Sa is not the voice of the keyword, the speech recognition processor 120 does not generate the second interrupt signal INT2 to the main processor 130 and the speech recognition processor 120 is disabled again. Meanwhile, the detection phase of the voice wakeup detecting device 100 is changed from the second detection phase to the first detection phase. In the first detection phase, the front end detecting circuit 110 continuously detects whether the first interrupt signal INT1 is asserted.
In the third detection phase, the main processor 130 is enabled and thus the smart phone is in the normal working state.
From the above discussions, the front end detecting circuit 110 of the smart phone in the first detection phase only judges the voice event of the voice signal Sa but does not recognize the keyword of the voice signal Sa. In the second detection phase, the speech recognition processor 120 starts to recognize the keyword of the voice signal Sa.
Since the front end detecting circuit 110 of the voice wakeup detecting device 100 is enabled only in the first detection phase, the power consumption is the lowest (e.g., about 1 mA). Since the front end detecting circuit 110 and the speech recognition processor 120 are both enabled in the second detection phase, the power consumption is increased (e.g., 6 mA).
However, the conventional voice wakeup detecting device 100 still has some drawbacks. For example, in case that the smart phone in the sleep state is placed in a noisy environment, the microphone 102 continuously receives the non-keyword voice. That is, the front end detecting circuit 110 may often assert the first interrupt signal INT1 due to noise trigging. Consequently, the detection phase of the conventional voice wakeup detecting device 100 is often switched between the first detection phase and the second detection phase. In other words, the use power consumption in a day is very huge.